Read e-book online A Comparison of the Bayesian and Frequentist Approaches to PDF

By Francisco J. Samaniego

ISBN-10: 1441959408

ISBN-13: 9781441959409

ISBN-10: 1461426197

ISBN-13: 9781461426196

This monograph contributes to the world of comparative statistical inference. cognizance is particular to the real subfield of statistical estimation. The booklet is meant for an viewers having a pretty good grounding in chance and facts on the point of the year-long undergraduate direction taken through information and arithmetic majors. the mandatory history on determination conception and the frequentist and Bayesian techniques to estimation is gifted and punctiliously mentioned in Chapters 1–3. The “threshold challenge” - choosing the boundary among Bayes estimators which are inclined to outperform typical frequentist estimators and Bayes estimators which don’t - is formulated in an analytically tractable manner in bankruptcy four. The formula features a particular (decision-theory established) criterion for evaluating estimators. the center-piece of the monograph is bankruptcy five during which, lower than fairly normal stipulations, an specific option to the edge is acquired for the matter of estimating a scalar parameter below squared mistakes loss. The six chapters that stick to deal with quite a few different contexts within which the edge challenge might be productively taken care of. incorporated are remedies of the Bayesian consensus challenge, the edge challenge for estimation difficulties regarding of multi-dimensional parameters and/or uneven loss, the estimation of nonidentifiable parameters, empirical Bayes equipment for combining info from ‘similar’ experiments and linear Bayes equipment for combining info from ‘related’ experiments. the ultimate bankruptcy presents an outline of the monograph’s highlights and a dialogue of components and difficulties wanting extra research.

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A Comparison of the Bayesian and Frequentist Approaches to Estimation (Springer Series in Statistics) by Francisco J. Samaniego


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